1. Field of the Invention
The present invention relates to an action recognition apparatus and method, a moving-object recognition apparatus and method, a device control apparatus and method, and a program.
2. Description of the Related Art
As a system or technique employing a known method for detecting a behavior pattern of a person based on images, there are disclosed a behavior detection system that automatically learns a probability model of standard behavior by the use of a hidden Markov model (e.g., Japanese Patent Laid-Open No. 11-259643 and U.S. Pat. No. 6,212,510) and a so-called gesture recognition technique (e.g., Japanese Patent Laid-Open No. 10-162151).
In addition, an applied technology that utilizes information about obtained behavior and an action pattern is proposed (e.g., Japanese Patent Laid-Open No. 8-257017, Japanese Patent Laid-Open No. 9-81309, Japanese Patent Laid-Open No. 9-161102, Japanese Patent Laid-Open No. 11-249773, Japanese Patent Laid-Open No. 2000-293685, Japanese Patent Laid-Open No. 2000-101898, Japanese Patent Publication No. 2801362, and Japanese Patent Publication No. 3140911). On the other hand, a method for performing person authentication from an action pattern is also proposed (e.g., Japanese Patent Laid-Open No. 2000-222361, Japanese Patent Laid-Open No. 2001-34764, and Japanese Patent Laid-Open No. 2001-202524).
Furthermore, there is also available an interface for identifying an operator through password analysis or fingerprint recognition to provide an operating screen suitable for the operator, as disclosed in Japanese Patent Laid-Open No. 10-149207. Unfortunately, in the above-described methods for detecting a behavior pattern and methods for using the information about the detected behavior pattern, a moving object, such as a subject person, cannot be identified to recognize and learn actions and states specific to the moving object. For example, with the method disclosed in the above-described Japanese Patent Laid-Open No. 9-161102, where individuals are identified based on their walking patterns, it is difficult to distinguish persons having similar walking patterns from each other. Therefore, it is difficult to automatically personalize a working environment, such as to provide individual environmental settings or individual settings related to operating procedures for and modes of various devices according to detected action patterns, such as gestures, of a particular person. With the above described known methods, it cannot also be expected to enable a system to automatically learn habitual or routine behavior specific to a particular person and the category of articles routinely used by the person.
With regard to the above-described known method for person authentication from action patterns, as the number of persons to be authenticated increases, it is necessary to specify the corresponding actions more strictly and the persons are required to pay more attention to faithfully reproduce actions registered for authentication. Thus, it is difficult to rely on action patterns only to perform successful person authentication.